Evidence map›Paper›PMID 30066031›Full record

ArticleJournal of medical systems2018

Patients Decision Aid System Based on FHIR Profiles.

Ilia Semenov, Georgy Kopanitsa, Dmitry Denisov, Yakovenko Alexandr, Roman Osenev, Yury Andreychuk

Abstract read
PubMed Publisher
In one paragraph

Article in Journal of medical systems, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
8citing papers in PubMed, 1 pooled it
3.2field-weighted citation impact, top 7% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

8 citing papers in PubMed, 1 synthesis or guideline pooled it, 19 citations in OpenAlex.

  1. Pooled it
  2. Article
  3. Article
  4. Review
  5. Article
  6. Experience in Developing an FHIR Medical Data Management Platform to Provide Clinical Decision Support.International journal of environmental research and public health · 2019
    Article
  7. Article
  8. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

6 authors at 1 institution in 1 country.

Ilia SemenovMedlinx LLC, Saint-Petersburg, Russia.
Georgy KopanitsaTomsk Polytechnic University, Lenina 30, 634050, Tomsk, Russia. georgy.kopanitsa@gmail.com.ORCID http://orcid.org/0000-0002-6231-8036
Dmitry DenisovMedlinx LLC, Saint-Petersburg, Russia.
Yakovenko AlexandrHelix Laboratory Service, Saint-Petersburg, Russia.
Roman OsenevMedlinx LLC, Saint-Petersburg, Russia.
Yury AndreychukMedlinx LLC, Saint-Petersburg, Russia.
National Research Tomsk State University · RU

Funding

Russian Scientific Fund n/a
6 · The paper itself

Abstract

Patients are becoming more and more involved in clinical decision-making process. Several factors support this process. Advances in omics allows individualization of diagnosis and treatment. Patient awareness and easy availability of data on the Internet allows patients to become informed decision makers when it comes even to disease management. Mass media emphasize the issue of medical errors, making patients demanding for quality in medical care. In some healthcare settings, patents face a problem of interpreting medical data and making decisions on treatment tactics without having a doctor, who could potentially support them. Delegating this task to a Patient Decision Aide system can add automatically generated recommendations to result reports without adding significant workload on the doctors, increase patients' motivation and support their decisions. We have implemented a patient decision aid system based on the productions rules, which: Collects data from available sources; Automatically analyses and interprets laboratory test results; Recommends running additional tests for a more precise diagnostic; Delivers automatically generated reports to doctors and patients in a natural language. To achieve semantic interoperability with other systems we have implemented a FHIR engine. The knowledge base has been organized as a graph structure. The application is structured as a set of lightly coupled services, which implement the logic of the decision support system. In total, we have modelled 365 nodes of test components, 5084 nodes of inference rules, 49932 connections and 3072 blocks of text for medical certificates. The findings of the research provide a deep understanding of how the semantically interoperable clinical decision support systems are implemented. Advances in notification the patients with the elements of patient decision aid is important for clinical data management, and for patients' empowerment and protection. We suppose that the system empowering patients in such way can play a meaningful role in helping patients to make informed decisions during the process of diagnostics and treatment.

Indexed as

Decision Support Systems, ClinicalPatient ParticipationDecision MakingDecision Support TechniquesHumansInternetDecision supportFirst order predicatesLaboratory information systemTelemedicine

Identifiers

PMID30066031
OpenAlexW2887931231

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.